Downscaling of surface air temperature over the Tibetan Plateau based on DEM

Abstract

Surface air temperature (Ta) is critical to the studies of radiation balance, energy budget, and water cycle. It is a necessary input for associated models. Most of the current Ta datasets of reanalysis products have limitations at local scales due to their coarse spatial resolutions. For better modeling the radiation balance, energy budget, and water cycle over the Tibetan Plateau, this study proposes a practical method for Ta downscaling based on the digital elevation model. This method is applied to downscale Ta of the China regional surface meteorological feature dataset (CRSMFD) at 0.1° and the ERA-interim (ERAI) product at 0.125° to 0.01°. The daily mean Ta and the 3-hourly instantaneous Ta with a 0.01° are obtained. The downscaled Ta are evaluated from the perspectives of accuracy and image quality. Results show that the daily mean Ta downscaled from the CRSMFD product has a RMSE of 1.13 ± 1.0 K at 105 meteorological stations and RMSEs of 0.96 K to 2.34 K at three experimental stations; the instantaneous Ta downscaled from CRSMFD has RMSEs of 1.02 K to 4.0 K at the three experimental stations. Ta after downscaling has better agreement with the ground measured Ta than before downscaling, especially in mountain areas. By contrast, Ta downscaled from the ERAI product has unacceptable accuracy due to the great uncertainty of the ERAI Ta over the Tibetan Plateau. With the proposed method, a 0.01° Ta dataset from 2000 to 2015 over the Tibetan Plateau was generated to satisfy related studies and applications.